~ Broaden your Horizon

A short note about “Business Intelligence” vs. “Analytics”

Are you aware that “Business Intelligence” and “(Advanced) Analytics” are actually completely different?

This should resolve the confusion for people who think that it´s actually the same, maybe because they are told so suggested by renaming of former “Business Intelligence” solutions, departments etc. to “Analytics”.

If one thinks that it´s just another name (“old wine in a new bottle”) he might not spend the time to find out that there is actually a difference and therefore he might not be aware of the new opportunities there are to innovate in his area and to really improve applications and solutions.

The information below is just a basic list of terminology to give you a quick start on this. Please be motivated to dig deeper.

“The analysis of all kinds of data using sophisticated quantitative methods (for example, statistics, descriptive and predictive data mining, simulation and optimization) to produce insights that traditional approaches to business intelligence (BI) – such as query and reporting – are unlikely to discover.”

Data mining (the analysis step of the “knowledge discovery in databases” process, or KDD), an interdisciplinary subfield of computer science is the computational process of discovering patterns in large data sets (“big data”) involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.

Machine learning is a subfield of computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Such algorithms operate by building a model from example inputs in order to make data-driven predictions or decisions, rather than following strictly static program instructions.

Predictive modeling leverages statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place.

Business reporting or enterprise reporting is “the public reporting of operating and financial data by a business enterprise,” or “the regular provision of information to decision-makers within an organization to support them in their work.” Reporting is a fundamental part of the larger movement towards improved business intelligence and knowledge management. Often implementation involves extract, transform, and load (ETL) procedures in coordination with a data warehouse and then using one or more reporting tools.

In management information systems, a dashboard is “an easy to read, often single page, real-time user interface, showing a graphical presentation of the current status (snapshot) and historical trends of an organization’s or computer appliances key performance indicators to enable instantaneous and informed decisions to be made at a glance.” In real-world terms, “dashboard” is another name for “progress report” or “report.” Often, the “dashboard” is displayed on a web page that is linked to a database which allows the report to be constantly updated.